基于CN05.1观测数据集， 评估了CMIP6数据在青藏高原腹地气温、 降水模拟能力， 预估了其5种气候模式7种情景在2015 -2100年的气温降水状况。研究表明： （1）历史时期（1961 -2014年）CMIP6数据气温降水观测值与模拟值偏差不大， 时空相关性强。（2）未来时期， 年均气温和降水整体呈现上升趋势， SSP3-7.0和SSP5-8.5情景2021 -2100年气温距平和降水量距平百分比增幅较大。气温距平高值区集中分布在柴达木盆地， 降水距平百分比高值区处于东南部澜沧江发源处。（3）四季中SSP5-8.5情景气温增幅最大； SSP3-7.0情景降水量夏季和冬季增幅最快， SSP5-8.5情景降水量春季和秋季增幅最快。（4）除SSP1-1.9外， 从近期到末期各情景气温均具有很强的时空相似性； 降水增幅夏季增幅最大， 冬季增幅最小， 具有很强的季节性和区域性差异。

The hinterland of the Qinghai-Xizang （Tibet） Plateau is affected by two major circulation systems， Westerly Wind and Indian Ocean monsoon.The average altitude of the region is high， and the terrain is complex and changeable.It is extremely complicated that the temperature and precipitation conditions in this region as a comparison to other areas of the Qinghai-Xizang （Tibet） Plateau.In order to accurately obtain the temporal and spatial changes of temperature and precipitation in this region and predict future temperature and precipitation changes， based on the CN05.1 observation dataset， the ability of CMIP6 data to simulate temperature and precipitation in the hinterland of the Qinghai-Xizang （Tibet） Plateau was evaluated.CMIP6 was corrected using Spatial Disaggregation and Equidistant Cumulative Distribution Functions Method Temperature and precipitation conditions of 5 climate models and 7 scenarios in 2015-2100 were estimated.The results show that： （1） In the historical period （from 1961 to 2014）， the temperature and precipitation observation values of CMIP6 data have little deviation from the simulation values， and have strong space-time correlation.（2） In the future （from 2021 to 2100）， the annual average temperature and precipitation will show an overall upward trend.The percentage of temperature anomaly and precipitation anomaly in 2021-2100 of SSP3-7.0 and SSP5-8.5 scenarios increased significantly.The high value of temperatures anomaly is concentrated in the Qaidam Basin， and the high value of precipitation anomaly is located at the source of the Lancang River in the southeast.（3） In the future， the temperature will continue to increase in the four seasons， the precipitation will also show an overall trend of rise in four seasons.However， the degree of precipitation increase is distinct in different seasons and different scenarios.In the four seasons， the temperature increase of SSP5-8.5 scenario is the largest.The temperature of SSP5-8.5 scenario increases fastest in autumn； The precipitation of SSP3-7.0 scenario increases fastest in summer and winter， while that of SSP5-8.5 scenario increases fastest in spring and autumn.（4） Except for the SSP1-1.9 scenario， the temperature of each scenario from the recent period to the end of the period shows strong temporal and spatial similarity.Against to the historical period， the spatial distribution of temperature in spring and winter showed a consistently rising tendency is similar， and that in summer and autumn is similar.The precipitation increase is the largest in summer and the smallest in winter.Compared with the historical period， the spatial distribution of precipitation anomaly percentage shows a strong seasonality and regional feature.The high value area is mainly distributed in the southeast of the study area.